Advanced Analytics: Digital Forensics
After learning about digital forensics related to cybersecurity, aspiring data scientists can:
- Gain a fundamental understanding of forensic based data science problems
- Become fluent in natural language processing techniques for insider threat analysis with the help of a scripting language
- Better understand the procedure for a digital investigation
- Investigate and solve problems in the cybersecurity realm utilizing data science techniques
Please note that successful completion of this course is a required component of the CERT Applied Data Science for Cybersecurity Professional Certificate. To learn more about these certificates and package pricing for the courses, please go to: SEI Certificates.
- Those with a particular interest in data science and cybersecurity, but limited experience with both concepts.
After successful completion of this course, you will:
- be able to identify the PRAVARA method
- have an appreciation for the nuance and complexity of a digital investigation and data science as a whole
- explain the relevance of deepfakes to modern data science
- explain the differences between types of deepfake techniques
- explain the concept of a neural network
- complete tasks involving natural language processing related to insider threat analysis
- complete tasks related to the deepfake detection process
In this course, students will learn about and investigate forensic techniques and concepts relied upon in the cybersecurity realm. These include:
- fundamentals of digital forensics
- crimes with digital assets
- PRAVARA and a digital investigation
- neural networks
- natural language processing techniques related to insider threat analysis through email
These concepts will be exercised in labs involving deepfake video detection and insider threat analysis.
This course is presented in the form of video instruction presented by experts from the SEI CERT Division. Downloadable materials include course presentation slides, instructions for lab exercises, jupyter license, and instructions for using a jupyter notebook. Learners will also be able to access additional resources related to the subject matter.
Before registering for this course, participants must complete the Fundamentals of Statistics Applied to Cybersecurity course.
Learners should have some exposure to digital forensics in itself and a working knowledge of a programming language (preferably Python or R). A working knowledge of calculus and linear algebra is helpful.
To access the SEI Learning Portal, your computer must have the following:
- For optimum viewing, we recommend using the following browsers: Microsoft Edge, Mozilla Firefox, Google Chrome, Safari
- These browsers are supported on the following operating systems: Microsoft Windows 8 (or higher), OSX (Last two major releases), Most Linux Distributions
- Mobile Operating Systems: iOS 9, Android 6.0
- Microsoft Edge, Firefox, Chrome and Safari follow a continuous release policy that makes difficult to fix a minimum version. For this reason, following the market recommendation we will support the last 2 major version of each of these browsers. Please note that as of January 2018, we do not support Safari on Windows.
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Training courses provided by the SEI are not academic courses for academic credit toward a degree. Any certificates provided are evidence of the completion of the courses and are not official academic credentials. For more information about SEI training courses, see Registration Terms and Conditions and Confidentiality of Course Records.